Data Engineer
David Protein Open At a glance
Mid-level Data Engineering role at David Protein. New York · $150,000–$200,000 OTE.
dataroles summary, based on the employer's posting.
What you'll do
- Move operational data from NetSuite, Shopify and retail sources into BigQuery, with quality checks and alerts
- Shape dbt models around sales, inventory, fulfillment, finances and the in-house S&OP platform
- Translate needs from Finance, Retail, Supply Chain and Growth into data solutions and shared modeling standards
- Create AI-assisted steps for parsing documents and classifying data, then test their accuracy with human review
- Build small tools and reporting automations, while helping maintain shared metrics and leadership dashboards
What you bring
- At least two years in data engineering, analytics engineering or a related technical field
- You can use SQL to model messy operational data, including dimensional structures and incremental updates
- You have shipped dbt work and used a cloud warehouse professionally
- You write Python for data workflows and automation, with testing and version control, and can work with current AI tools
Who this fits
This mid-level, full-time role suits someone comfortable owning work independently and keeping teammates informed about priorities. You’ll work from the New York City office five days each week.
From the employer
Company:
David creates tools to increase muscle and decrease fat. Our first product is a protein bar. More broadly, David is a platform to develop high-protein, low-calorie, blood-sugar-friendly foods that are craveable.
This is a compelling opportunity to join an exciting new food brand as we enter a critical growth stage. David is led by CEO Peter Rahal, the Cofounder and Former CEO of RXBAR ($600M exit to Kellogg in 2017). We have strong aspirations to become the most popular high-protein bar in North America and beyond.
Roles & Responsibilities:
The Data Engineer will co-own David's data infrastructure and build AI-powered workflows that eliminate manual, repetitive work across the organization. This role sits at the center of how the company turns operational data from our ERP, retail platforms, e-commerce channels, finance platforms, and supply chain systems into reliable pipelines, trusted data models, and automated workflows that are leveraged cross-functionally.
Data pipelines & modeling
- Design, build, and maintain ETL pipelines from source systems (NetSuite, Shopify, retail platforms/EDI, etc) into BigQuery, with automated testing, monitoring, and alerting for data quality.
- Develop canonical, well-documented dbt models for spanning sales, inventory, fulfillment, financials, and our in-house S&OP platform that serve as the trusted foundation for reporting and analytics.
- Partner with Finance, Retail, Supply Chain, and Growth to turn business requirements into data solutions, and help set standards for modeling, documentation, and governance.
- Co-own our semantic layer and BI tooling (Omni): model curation, metric definitions, and the reporting leadership relies on.
Internal tooling & automation
- Design and deploy AI-powered workflows for document parsing, data extraction, classification, and enrichment as part of data pipelines and operational processes.
- Implement evaluation frameworks and human-in-the-loop patterns to ensure reliability and accuracy of AI-driven outputs.
- Manage credentials, sensitive data, and third-party integrations, and design workflows with appropriate access controls and guardrails.
- Build scripts, automations, and lightweight internal tools that replace manual processes, working alongside engineers who own application development.
- Automate recurring reporting and ad hoc analyses to support organizational visibility to key metrics.
Requirements
- 2+ years of professional experience in data engineering, analytics engineering, or a closely related technical role.
- Technical proficiency:
- Strong SQL and data modeling skills: you can design clean, well-documented models from messy operational and ERP data, and you understand dimensional modeling and incremental transformation patterns.
- Production experience with dbt and a cloud data warehouse.
- Proficiency in Python for pipelines, automation, and data workflows: clean, testable code with proper version control.
- Working fluency with modern AI tooling.
- Nice to have: TypeScript and full-stack experience (Next.js/React, Postgres), agent frameworks and orchestration, semantic layer / BI modeling (Omni, Looker), and experience with ERP, supply chain, or CPG data.
- A track record of building pipelines, systems, or automations that other people actually depend on in a professional setting, a side project, or an open-source contribution.
- The ability to operate independently while clearly communicating priorities and initiatives to the rest of the team.
- Humble, self-aware, and curious.
- A desire to build an early stage CPG company with a mission to help people increase muscle and decrease fat.
Benefits
- This is a full-time role.
- Salary: $150K - $200K per year, inclusive of cash bonus based on attainment of company targets
- Company equity opportunity
- 100% covered Health, Vision, Dental Insurance
- 401(k)
- Additional perks, such as covered gym expenses
- Substantial and required PTO
- We work in the office 5 days per week in New York City – when culture lines up, it is fun to be in the office together.
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